Triple
T15090799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Níðhöggr |
E360407
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Náströnd |
E365499
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Náströnd | Statement: [Níðhöggr, associatedWith, Náströnd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Náströnd Context triple: [Níðhöggr, associatedWith, Náströnd]
-
A.
Náströnd
chosen
Náströnd is a grim shore in Norse mythology where the souls of the most wicked are punished in a hall woven of serpents and dripping venom.
-
B.
Lysekil
Lysekil is a coastal town in western Sweden known for its picturesque archipelago, fishing heritage, and popular seaside tourism.
-
C.
Härnösand
Härnösand is a coastal city in northern Sweden known for its historic architecture, maritime heritage, and role as an administrative and cultural center in the region.
-
D.
Hammarö
Hammarö is a Swedish island and municipality in Värmland County, known for its forests, coastline, and proximity to the city of Karlstad.
-
E.
Bruntinge
Bruntinge is a small village located in the municipality of Midden-Drenthe in the Dutch province of Drenthe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027925788190b955fdc6626adf7d |
completed | April 15, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae1d7a0c819096b035f8ca8d0e90 |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:04 a.m.